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@phdthesis{phong2015:phd,

author = {Foncubierta Rodriguez, Antonio},
title = {Description and retrieval of medical visual information based on language modelling},
school = {Viper group, CS Department, University of Geneva},
year = 2014,
month = {Sep},
      url = {https://archive-ouverte.unige.ch/unige:46981}
}

@phdthesis{phong2015:phd,

author = {Nguyen, Phong},
title = {Meta-mining: a meta-learning framework to support the recommendation, planning and optimization of data mining workflows},
school = {Viper group, CS Department, University of Geneva},
year = 2015,
month = {Sep},
      url = {https://archive-ouverte.unige.ch/unige:86131}
}

@phdthesis{deherrera2015:phd,

author = {Garcia Seco De Herrera, Alba},
title = {Use case oriented medical visual information retrieval & system evaluation},
school = {Viper group, CS Department, University of Geneva},
year = 2015,
month = {Apr},
      url = {https://archive-ouverte.unige.ch/unige:73184}
}

@phdthesis{garg2015:phd,

author = {Garg, Nikhil},
title = {Generative models for syntactic and semantic structure prediction using latent variables},
school = {Viper group, CS Department, University of Geneva},
year = 2015,
month = {Nov},
      url = {https://archive-ouverte.unige.ch/unige:88095}
}
@phdthesis{farahmand2017:phd,
author = {Farahmand, Meghdad},
title = {Computational models of learning the idiosyncrasy of multiword expressions},
school = {Viper group, CS Department, University of Geneva},
year = 2017,
month = {July},
      url = {https://archive-ouverte.unige.ch/unige:96989}
}
@phdthesis{deltoro2017:phd,
author = {Jimenez Del Toro, Oscar},
title = {Quantitative analysis of medical images: finding relevant regions-of-interest for medical decision support},
school = {Viper group, CS Department, University of Geneva},
year = 2017,
month = {May},
      url = {https://archive-ouverte.unige.ch/unige:96297}
}
@phdthesis{dicente2018:phd,
author = {Dicente Cid, Yashin},
title = {Lung tissue analysis: from local visual descriptors to global modeling},
school = {Viper group, CS Department, University of Geneva},
year = 2018,
month = {Aug.},
      url = {https://archive-ouverte.unige.ch/unige:111394}
}
@phdthesis{sun2015:phd,
author = {Ke Sun},
title = {Information Geometry and Data Manifold Representations},
school = {Viper group, CS Department, University of Geneva},
year = 2015,
month = {Dec.},
      url = {https://archive-ouverte.unige.ch/}
}
@phdthesis{mohamed2014:phd,
author = {Hisham Mohamed},
title = {Scalable approximate k-NN in multidimensional big data},
school = {Viper group, CS Department, University of Geneva},
year = 2014,
month = {Aug.},
      url = {https://archive-ouverte.unige.ch/unige:40731}
}
@phdthesis{markonis2014:phd,
author = {Dimitrios Markonis},
title = {User-oriented medical image retrieval},
school = {Viper group, CS Department, University of Geneva / HEVs Valais},
year = 2014,
month = {Nov.},
      url = {https://archive-ouverte.unige.ch/unige:43325}
}
@phdthesis{szekely2011:phd,
author = {Eniko Szekely},
title = {Dimension reduction for clustered high-dimensional data},
school = {Viper group, CS Department, University of Geneva},
year = 2011,
month = {Mar.},
      url = {https://archive-ouverte.unige.ch/unige:17343}
}
@phdthesis{morrison2011:phd,
author = {Donn Morrison},
title = {Latent variable modelling of user interaction in image retrieval},
school = {Viper group, CS Department, University of Geneva},
year = 2011,
month = {Feb.},
      url = {http://archive-ouverte.unige.ch/vital/access/manager/Repository/unige:15947}
}
@phdthesis{Janvier2007:phd,
author = {Bruno Janvier},
title = {Towards Automatic Semantic Multimedia Structuring and Retrieval},
school = {Viper group, CS Department, University of Geneva},
year = 2007,
month = {Jan.},
      url = {http://archive-ouverte.unige.ch/vital/access/manager/Repository/unige:2344}
}
@phdthesis{Kludas2010:phd,
author = {Jana Kludas},
title = {Information Fusion for Multimedia exploiting Feature Interactions for Semantic Feature Selection and Construction},
school = {Viper group, CS Department, University of Geneva},
year = 2010,
month = {Dec.},
      url = {http://archive-ouverte.unige.ch/vital/access/manager/Repository/unige:14539}
}
@phdthesis{kosinov2005:phd,
author = {Serhiy Kosinov},
title = {Machine Learning Approach to Semantic Augmentation of Multimedia Documents for Efficient Access and Retrieval},
school = {Viper group, CS Department, University of Geneva},
year = 2005,
month = {Dec.},
}
@phdthesis{moenne2005:phd,
author = {Nicolas Mo\"enne-Loccoz},
title = {Dynamiques des Composantes Visuelles pour la Gestion de Documents Vid \'eo par le Contenu},
school = {Viper group, CS Department, University of Geneva},
year = 2005,
month = {Dec.},
      url = {http://archive-ouverte.unige.ch/vital/access/manager/Repository/unige:2323}
}
@phdthesis{VG:MulH2002,
author = {Henning M{\"u}ller},
title = {User interaction and evaluation in content-based visual information retrieval},
school = {Viper group, CS Department, University of Geneva},
year = 2002,
address = {Geneva, Switzerland},
month = {June},
vgproject = {viper}
}
@phdthesis{VG:Mul2001,
author = {Wolfgang M{\"u}ller},
title = {Design and implementation of a flexible Content--Based Image Retrieval Framework - The GNU Image Finding Tool},
school = {Viper group, CS Department, University of Geneva},
year = 2001,
address = {Geneva, Switzerland},
month = {September},
vgproject = {viper}
}
@phdthesis{VG:Rau1998,
author = {Christian Rauber},
title = {Acquisition, archivage et recherche de documents accessibles par
	le contenu: application \`a la gestion d'une base de donn\'ees d'images
	de filigranes},
school = {University of Geneva},
year = {1998},
type = {{P}h.{D}. {D}issertation {N}o. 2988},
address = {Switzerland},
month = {March},
url = {http://cui.unige.ch/~rauber/these/index.htm},
vgclass = {thesis},
vgproject = {cbir}
}
@phdthesis{VG:Sta1998,
author = {Sergei Startchik},
title = {Geometric and Illumination Invariant Object Representation: Application
	to Content-based Image Retrieval},
school = {University of Geneva},
year = {1998},
type = {{P}h.{D}. {D}issertation {N}o. 3009},
address = {Switzerland},
month = {July},
note = {Thesis Jury: Prof. Thierry Pun (Geneva, CH), Prof. Roger Mohr (INP
	Grenoble, F), Serge Ayer (EPF-Lausanne, CH), Prof. Christian Pellegrini
	(Geneva, CH)},
url = {http://cui.unige.ch/~startchi/PhD/},
abstract = {This work addresses several issues in the field of computer vision.
	In particular, attention is focussed on the problem of the representation
	of an object from its appearance in an image. Several advances are
	proposed for the representation of planar shapes, which are thus
	suitable for representing planar and faceted objects. The representation
	developed is employed for content-based retrieval from an image database.
	The proposed projectively invariant description for groups of planar
	disjoint contours as a simultaneous polar reparametrization of multiple
	curves. Its origin is an invariant point and, for each ray orientation,
	the cross-ratio of the intersections with the closest curves gives
	the radius. The sequence of cross-ratio values for all orientations
	forms a signature. With respect to other methods, this representation
	is less reliant on individual curve properties, both for the construction
	of the reference frame and for the calculation of the signature.
	At the same time, this representation is local and integrates information
	from multiple curves, guaranteeing robustness to curve discontinuities
	and partial occlusions. Chromatic information is introduced into
	the representation and offers two advantages. First, the representation
	provides a more complete description of the shape and thus becomes
	more discriminative. Secondly, the chromatic description is illumination
	invariant under a diagonal chromaticity model and one more acquisition
	variable is therefore removed. The proposed representation was originally
	developed for planar shapes, but an extension has been proposed and
	validated for trihedral corners. [truncated]},
abstract2 = {A complete system architecture has been implemented, composed of the
	following stages: feature extraction, reference frame construction,
	signature evaluation and indexing. The feature extraction stage provides
	a set of image contours approximated by splines. Joint invariant
	properties of curves are used to define the center point of the reference
	frame and the associated rays. Invariant signatures are computed
	from a combination of local properties of multiple curves. These
	signatures are used as a multidimensional index into a database of
	signatures and a subset of plausible object models is thus obtained.
	The invariant signature method has been used for object representation
	in the context of content-based retrieval from image databases. In
	particular, we focus on images which portray man-made objects with
	planar facets or trihedral corners, which contain trademarks. The
	database consist of 203 images of 41 such objects. Images were taken
	from different viewpoints under various illumination conditions.
	Experimental evaluation has shown that the method is stable to those
	realistic variations and its performance in this framework is satisfactory.
	In conclusion, we believe that this approach is an important extension
	of shape representation methods to a much broader class of objects.},
vgclass = {thesis},
vgproject = {cbir}
}
bib/viper_phd.1543331895.txt.gz · Last modified: 2018/11/27 16:18 by marchand
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Keywords: machine learning, information geometry, data mining, Big Data, affective information retrieval (recherche d'information), information visualisation, content-based image and video retrieval (CBIR, CBR, CBVR, CBMR, CBMIR), information mining, classification, multimedia and multimodal information management, semantic web, knowledge base (RDF, OWL, XML, metadata, auto-annotation, description), multimodal information fusion